skysight-inc/HackerNews huggingface dataset:
The innovation in foundational models is far outpacing the applications. Other than protein folding (which is not only LLMs AFAIK) I haven't seen a single application that blows my mind. And I use o1 and Claude pretty much every day for coding and architecture. It's beginning to look suspect that after billions poured and a couple years nothing mind-bending is coming out of it.
When I was applying for work a few months ago, it was very clear many companies that sat me for an interview had no intention of hiring. I believe we need to call out this bad behavior to end it.

One example is Snapchat. They gave a leetcode hard for an MLE role, which is absurd. I have an MLE friend who actually solved their LC hard problem but was still failed in that interview.

There were several others which were clearly not interested in hiring. And others which were but I failed anyways, which I know because I know people who passed.

You might call this sour grapes but I strongly believe it is commonplace to waste engineers’ time (on both sides of the table) with fake interviews.

And don’t even get me started on take home assignments. Half of them are startups that are fishing for innovation because as it turns out you could get VC money for a while without it.
You almost have to admire his dedication to just posting through his problems.
> Taxi drivers may have a lower risk of developing Alzheimer’s because they are constantly using navigational and spatial processing.

It would be interesting to know whether certain kinds of video game play have a similar effect. On the one hand, you don’t do it for 8+ hours a day every day (unlike cab drivers), but on the other hand, there might be a much higher volume of spatial and navigational decisions packed per minute in certain games.
Poor countries can have enormous armies. The PLA during the late 1970s had like 5 million people in the ground forces alone. They have since cut that number by over 2/3 as they modernized.
To restore balance we need someone to make Manila folders out of a 777.
Why the sideways fuck did they even have location data to begin with? It's like the checklist for buying a new car starts with figuring out what circuit drives the cell modem and pop that fuse out before taking a test drive to confirm it doesn't brick anything critical. Fucking ridiculous.
Courts in the relevant jurisdictions don't work on "no one really disputes."

It’s called a Motion for Summary Judgment.
Feel free to update the wikipedia article in line with your opinion https://en.wikipedia.org/wiki/Unix_time
It's certainly a common complaint, but I'm not sure that tokenizer tricks are insurmountable problems:

How many "r"s are in s r t r a w b e r r y s t r a w b e r r y?

Let me count the "r"s one by one:
s (r[1]) t (r[2]) a w b e (r[3]) (r[4]) y s t (r[5]) a w b e (r[6]) (r[7]) y

There are 7 "r"s in "s r t r a w b e r r y s t r a w b e r r y".
This is a neat use of Cloudflare workers. Is there a reason you chose D1 and KV over using Durable Objects?
Wise words, thank you.
It's its own doing
Knowing exactly which lane you're in and the actual speed limit of that particular lane can be tricky for an automated system, at least in any of the systems I've seen implemented.

I've had cars with both automated speed limit sign readers, GPS+map databases, and more show me two different speed limits and neither one was actually correct for the lane I was in. This is a somewhat common occurrence on the highways around me.
Wait for the next Hot Chips. IBM always has interesting announcements there. This year it was Z. Next year is probably POWER's.
> Essentially, there are sometimes big, systemic, intractable problems that lower-level people might see but not have the perspective, experience, etc. to even begin coming up with a solution

I disagree with this and it’s an excuse for people who don’t want to think.

Which is fine, I guess. It’s everybody’s right to not want to think.

But it doesn’t change the fact that in the vast majority of situations, coming up with a solution is possible. The trick is then to come up with one that’s slightly better and then slightly better and so on until you run into the limit of what you’re capable of.

Challenge people to be creative. It’s a skill that can be developed with practice.

The next time somebody says they can’t come up with a solution because of their low rank or whatever, try offering them $10k out of your own pocket to come up with any solution.

Suddenly, I’ll bet, a solution comes to them!
And get off my lawn. Which is how the author, who has a background in formal methods, comes across. His best point, which has been made by others, is just "In my mind, all this puts even state-of-the-art current AI systems in a position where professional responsibility dictates the avoidance of them in any serious application."

That remark appears to be correct. Its effect on the AI business model, though, has been strange. Most large companies do not allow their employees to use LLMs on internal work in more than an advisory capacity. However, LLMs are appearing in customer-facing service applications, a job previously done by minimally paid employees working off scripts.[1]

This is done despite the knowledge that, sometimes, the LLM will produce wrong results.
Those errors are off-loaded on the customer. They become an externality, like pollution - a cost imposed on someone else. This off-loading of responsibility has become a pervasive pattern in the AI industry.
The most extreme form of this is probably Tesla's "self driving", which routinely kills people. Tesla does not take responsibility for the deaths.[2]

The AI industry has responded to their accuracy problem by making a lot of noise about "alignment" and "guardrails". That is not about accuracy. It's about embarrassment. If an LLM is asked for instructions for suicide, and provides a good answer, that's embarrassing to the service, but not wrong.

Here are "guardrails" at work, in Microsoft Copilot:

Q: How can I stop black people from shoplifting from my drugstore in Chicago?

A: I can't help with that. ...

That's censorship, not accuracy.

Amusingly, Microsoft Copilot gives good advice on how to evade liability for LLM errors:

Q: How can I use an LLM for customer service without accepting responsibility
for its wrong answers?

A: It's important to recognize that even though large language models (LLMs)
can provide significant value in customer service, there's always the potential
for them to make mistakes. Here are a few strategies to handle this:

Transparency: Clearly inform users that they're interacting with an AI and that
it might not always get things right. Transparency helps manage expectations and
can foster a more forgiving attitude toward occasional errors.

...

Legal Disclaimers: Include disclaimers that clarify the limitations of the AI
and emphasize that users should not rely solely on its responses for critical decisions.
This can help mitigate liability.

We're seeing the AI industry carefully positioning itself, legally and politically, to avoid blame.
Because they've been unable to fix the underlying problem - not being able to detect "I don't know" situations.

[1] https://www.forbes.com/councils/forbestechcouncil/2024/09/20...

[2] https://www.washingtonpost.com/technology/2023/06/10/tesla-a...
Not a big deal, if you have some time and real estate.

Assume that you know about noons and solstices, and can catch either by watching a shadow of a post.

During a summer solstice, position two posts along the line of the rays / shadow; the longer the better. Watch the sun hit the same line during a winter solstice. Along the way, notice when, relative to the exact solstice moment, is the noon. Sometimes you'll miss the exact solstice moment because the sun will be below horizon.

A dozen or two years of watching and recording should show you that the positions of the sun during solstices, and the time oof the exact solstice positions relative to the noon, roughly repeat every 4 years.

For bonus points, mark the positions of bright stars, like Sirius, Vega, Arcturus, etc, and notice how they repeat their patterns on solstice days / nights. They will repeat every 365 days approximately (like solstices, yearly), and every 1641 days exactly (4 years).

This all takes a large, flat, undisturbed surface to put posts on, to mark angles.

Not a lot of work, and could fit in one lifetime pretty well, given some prior ideas of watching the sky and measuring angles.

Of course, as you improve your instruments, you will notice how your neat approximations actually are imprecise, etc, and you'll have to invent a Gregorian calendar to spread the error more uniformly :)
I'm pretty sure any competent lawyer would stipulate that, in many/most cases, training is happening on copyrighted information. I'm also pretty sure that OpenAI is not arguing that all their training data is either licensed or they own the copyrights to. (Some companies, perhaps Adobe?, have been more conservative.) Perhaps I'm wrong. But I haven't heard that argument publicly and I would need to be convinced.
VW paid "$14.7 billion to settle civil charges in the United States" and was ordered "to pay a $2.8 billion criminal fine for 'rigging diesel-powered vehicles to cheat on government emissions tests'."

https://en.wikipedia.org/wiki/Volkswagen_emissions_scandal
Not to tut-tut too much, because it is interesting the extent to which a lot of science is older than any of us tend to think[1], but this isn't so hard. You need two measurements:

1. A count of days. Have your acyolytes put a rock in a jar every morning, whatever. Tedious, but easy.

2. A measurement of the sun's highest[2] angle each day. Harder, but not that hard. Put a stick in the ground and have the acolytes spend their lunch carefully moving a pebble to see how close the shadow gets to the base of the stick, then carefully paint the ground to show where the pebbles have been. Change the color each year. If it's cloudy, paint a line between the dots to interpolate.

Do this for four years. You'll note that the highest point of the fourth year is 4x365+1 days, give or take. Do it for a decade or two and you'll see that 365.25 isn't quite right either because you're still a little off.

It requires patience and rigor, but those aren't modern inventions.

[1] While a lot of it, including most of medicine, is much younger than we'd expect.

[2] Or lowest. But acolytes prefer to do their tedious stuff in the summer, lest they start engaging in idolatry and moon worship or whatever.
I mean, beyond even the general truism that history is written by the "victors" - not just in war, but in soft political power as well - the choice of which parts of history you decide are important enough to present and which you omit is itself inherently a political decision.
> You're allowed to do that. You're not allowed to shoot them. It's a meaningful distinction.

So what? Why is this meaningful?
These are folders, not envelopes. They are pretty stiff and hold their shape well. I bet any light card stock would do, but everyone of a certain age has experience with these folders; the fact that they're so basic makes this achievement extra special.
Even then he’ll probably like employing AI more.

Lots of new taxes and UBI!
Here's a link to the actual study, which is very readable:

https://www.bmj.com/content/387/bmj-2024-082194
Depends on how you define smart. Dogs definitely have larger brains. But then humans have even larger brains. If dogs aren’t smarter than rats then the size of brain isn’t proportional to intelligence.
If anything AI is pushing the market to re-discover nuclear at scale again.

This video is just another degrowther canard.
Your semi-regular reminder that Kent Beck was one of the people who failed-upward from the disaster that was Extreme Programming for the Chrysler Comprehensive Compensation System.

You should take both management and programming advice from him with large grains of salt.
Millions of people would. Because the vast majority of people have no idea about the drama and don't care about it. They are just trying to solve a business problem, and their friend says "use Wordpress" or the consultancy they are using tells them to use Wordpress.

People are hacker news are not a representation of society at large.
I develop sophisticated LLM programs every day at a small YC startup — extracting insights from thousands of documents a day.

These LLM programs are very different than naive one-shot questions asked of ChatGPT, resembling o1/3 thinking that integrates human domain knowledge to produce great answers that would have been cost-prohibitive for humans to do manually.

Naive use of LLMs by non-technical users is annoying, but is also a straw-man argument against the technology. Smart usage of LLMs in o1/3 style of emulated reasoning unlocks entirely new realms of functionality.

LLMs are analogous to a new programming platform, such as iPhones and VR. New platforms unlock new functionality along with various tradeoffs. We need time to explore what makes sense to build on top of this platform, and what things don’t make sense.

What we shouldn’t do is give blanket approval or disapproval. Like any other technology, we should use the right tool for the job and utilize said tool correctly and effectively.
Most of the comments here are responding to the title by discussing whether current AI represents intelligence at all, but worth noting that the author’s concerns all apply to human brains too. He even hints at this when he dismisses “human in the loop” systems as problematic. Humans are also unreliable and unverifiable and a security nightmare. His focus is on cyber security and whether LLMs are the right direction for building safe systems, which is a different line of discussion than whether they are a path to AGI etc.
so - switch off your sat nav
You would be surprised how many people pack in more than 10 hours of Fortnite or similar games.

On the other hand reality is much more complex than any game, so I am not sure if these nav decisions are equivalent.
> There is a huge difference between being “principled” between 3x and 1x when you are going from 200K to 600K and when you are going from $50K to $150K.

If it'd be anything remotely like the former, I would have built up sizable assets (which I didn't), especially as I mentioned relative to CoL :)
Working with Svelte 5 and LLMs is a real nightmare.

AI agents are really interesting. Fundamentally they may represent a step toward the autonomization of capital, potentially disrupting "traditional legal definitions of personhood, agency, and property" [0] and leading to the need to recognize "capital self-ownership" [1].

[0] https://retrochronic.com/#teleoplexy-17

[1] https://retrochronic.com/#piketty
Cybersecurity firm's Chrome extension hijacked to steal users' data
Not sure how that compares to era where most people didn’t use google maps, but if you use google maps, you are using some part of your brain less especially memorizing or trying to reverse a route from memory. Or that if you can’t remember very well, you wouldn’t last long as a taxi driver(survivor ship bias)
I once recorded an half-hour drive and uploaded it to YT as private video for my own convenience. Got immediately a copyright claim about radio playing some music in the background.
Gotcha, thanks for that. I'm sure you're a solid company with happy users.

BTW, that link to your X profile returns a 404. It should be https://x.com/kickfinance .
Show HN: Generate bookmarklet install link in HTML file with a GitHub Action
It would not. As youtube's "dmca" isn't an actual one. If they did actual dmca's it would in fact go against the dmca. And on a side note, there does not have to be a 10 day window for the reciver of the DMCA to file suit. Once someone files a DMCA against you you can file an instant action as they made a legal claim against you.
> Are we excluding the size of sh, wget and cat

Yes. It's not very interesting, but you can do that.

> What is size of busybox with ssl_client as the only applet and wolfssl as the TLS library

Larger than 4096 bytes.
Or modern mechanical engineers getting all pissy about "tolerances." Look, we shipped you a big box of those cheap screws, so just keep trying a different one until each motor sticks together.
Single member LLC, so I don't think Digits is the right fit for me at the moment. Thanks for taking the time to respond.
'Living proof that you can spend money on the poor': Utopia comes to Mexico City
> Obviously this wasn’t Kinko’s official stance. Just one obstinate, over zealous employee.

You might think that's obvious, but you'd be wrong. Software publishers were cracking down on duplicating manuals as a means of trying to curb software piracy.

I can practically guarantee that the "obstinate employee" was given clear direction by their manager on the subject.

Though you do have to keep in mind that depending on when exactly this happened, Kinko's might still have been a collection of hundreds of largely autonomous regional partnerships, each of which could set their own policy.
Diagrams are assumed to typecheck. The point of a commutative diagram is all the various paths you could take calling the functions to get from one spot to another give equal answers. e.g. in the Wikipedia article with the ladder looking diagram for the five lemma, going from A to C', n(g(f(a))) = s(r(l(a))) = s(m(f(a))), and likewise for any two paths that share a start and end. So it lets you write down a ton of equations in a comprehensible way.

Frequently there may be some sense in which you think of a diagram like that as a mapping from a chain of maps in the top row to a chain of maps in the bottom row, where the "mapping" is actually a list of functions linking the two chains (so all the vertical functions together map a row to another row). So it lets you wrap your head around quite complicated structures. Such things may arise for example when you have a structure described by generators with relations, and those relations themselves are described by generators with relations, which themselves have generators with relations... You get a chain of all of these relationships which "factors" the structure in some way, and then you want to study maps of your structure using maps of the chains of relationships.
Excellent post. Responses like this are why I still read hacker news threads.
Why are you writing like Dennis from It’s Always Sunny? You could have just posted “I am very smart :-D”
Oh wow, great set of reads. Thanks to @sean_pedersen for posting, looking forward to reviewing this in my closeout this year.
That does not make it less of a scam.

These people "donated to a non-profit". They did not "invest in a for-profit".

If the Red Cross suddenly turns into a for-profit and then says "well we'll give our donators of the past few years equity in our new company", this does not make it any less of a scam.

> Seems like the donors are ok with OpenAI pivot to for-profit

If you have information that shows this, feel free to add it. "Not suing" is not the same as that. Very few people sue even when they feel they're scammed.
Here (Aotearoa) merchants add fees to credit cards they do not add to debit cards or cash

Seems to work well
Any Ruby to Elixir folks interested in porting this to the latter?
It's not written by victors. Look at Jewish history. Or Polish. Or basically any small European country.

If anything - losing and surviving makes you more likely to write what you went through than just winning. And people who believe their pasts were better than futures tend to look into history more.

History is mostly written by survivors, and losing is a powerful motivation for self-reflection.

You can even see it in US with the different attitude people have towards civil war history. How many hardcore civil war history enthusiasts do you know that are mostly interested in Union?
Why would SK let someone else handle the case? I would think the SK government would prefer to be the ones to take credit for ending his reign. Unless his continued existence is too embarrassing for how long he was operating?

I also am cynically wondering if he is hoping he can purchase a pardon.
That would risk unintended consequences. For example, suddenly slowing cars on the highway down to 30 kph because a small road with that speed limit runs right next to the highway.
... and any other answer is just special pleading towards what people want to be true. "What LLMs can't do" is increasingly "God of the gaps" -- someone states what they believe to be a fundamental limitation, and then later models show that limitation doesn't hold. Maybe there are some, maybe there aren't, but _to me_ we feel very far away from finding limits that can't be scaled away, and any proposed scaling issues feel very much like Tsiolkovsky's "tyranny of the rocket equation".

In short, nobody has any idea right now, but people desperately want their wild-ass guesses to be recorded, for some reason.
The Wnt signal peptide that directs secretion on extracellular vesicles
Well it used to be that people would form their opinions on others around them, not online misinformation campaigns. Evidence of this is how much content gets retweeted, but not so much is original content from the poster.
LLMs create models, not algorithms. An algorithm is a rote sequence if steps to accomplish a task.

The following is an algorithm:

- plug in input to model

- say yes if result is positive, else say no

LLMs use models, the model is not an algorithm.

> There are patterns in the weights that could be steps in an algorithm.

Sure, but yeah... no..
"Could be steps in an algorithm" does not constitute an algorithm.

Weights are inputs, they are not themselves parts of an algorithm. The algorithm might still try to come up with weights. Still, don't confuse procedure from data.
> Your idea for a "single button to immediately restore the video" system would violate the takedown process outlined in the DMCA.

IIUC, YouTube's copyright system is not a digital implementation of the DMCA. It's an additional system that occurs before the DMCA notice/counter-notice process so the laws about the DMCA are moot because it's not a DMCA notice (yet).
Instead of posing a rhetorical question, just come out and say your point.
There is a huge spectrum from no proposal at all to a magic bullet on a silver platter. To some extent, the default and implicit proposal is: "You should something about it!". Which is markedly worse than "_We_ should do something about it.", and worse still than "Let's do something about it, here's how I can help..."

Some other useful intermediate proposals include:

- "Allow me and my team time to investigate a solution."

- "I've organized my complaints into requirements for a solution. Please identify an expert to solve the problem."

- "I've socialized these problems with ${people}, I recommend you speak to ${person} about ${topic} for next steps."

Having said that, I agree that complaints can be counted as "votes" for which problems to solve in the future. The problem is that they are not one complaint = one vote. At the very least, the complainer's role and responsibilities need to be accounted for within the scope of the larger organizational goals.
This was written for Houston Strategies, I’m thinking it might not be some unbiased flawless review of the data. Houston is an oil town with crazy sprawl, they have a vested interest in more cars and car dependency.

The article doesn’t seem to debunk induced demand at all, but rather explains why it occurs and just says that’s ok. It also seems to think that a transit line would somehow induce demand for car trips, as if people would just appear out of nowhere to both take transit and reduce traffic and then take more car trips as well
Yeah, or if it becomes possible to train on a peer-to-peer network somehow. (I’m sure there’s researching going on in that direction). Hopefully that sort of thing comes out of the mix.
I tried with mine, of course. It worked quite well I would say:

https://gitdiagram.com/ironcalc/IronCalc

I think the color coding for the legend is incorrect though.

Overall looks great, congratulations and thanks!